Transit least-squares survey -- II. Discovery and validation of 17 new sub- to super-Earth-sized planets in multi-planet systems from K2

The extended Kepler mission (K2) has revealed more than 500 transiting planets in roughly 500,000 stellar light curves. All of these were found either with the box least-squares algorithm or by visual inspection. Here we use our new transit least-squares (TLS) algorithm to search for additional planets around all K2 stars that are currently known to host at least one planet. We discover and statistically validate 17 new planets with radii ranging from about 0.7 Earth radii to roughly 2.2 Earth radii and a median radius of 1.18 Earth radii. EPIC201497682.03, with a radius of 0.692 (-0.048, +0.059) Earth radii, is the second smallest planet ever discovered with K2. The transit signatures of these 17 planets are typically 200 ppm deep (ranging from 100 ppm to 2000 ppm), and their orbital periods extend from about 0.7 d to 34 d with a median value of about 4 d. Fourteen of these 17 systems only had one known planet before, and they now join the growing number of multi-planet systems. Most stars in our sample have subsolar masses and radii. The small planetary radii in our sample are a direct result of the higher signal detection efficiency that TLS has compared to box-fitting algorithms in the shallow-transit regime. Our findings help in populating the period-radius diagram with small planets. Our discovery rate of about 3.7 % within the group of previously known K2 systems suggests that TLS can find over 100 additional Earth-sized planets in the data of the Kepler primary mission.Comment: published in A&A, 12 pages, 6 colored Figures, 1 Table; minor textual corrections; Fig. 5 corrected for the distance scalin

Transit least-squares survey - I. Discovery and validation of an Earth-sized planet in the four-planet system K2-32 near the 1:2:5:7 resonance

We apply, for the first time, the Transit Least Squares (TLS) algorithm to search for new transiting exoplanets. TLS is a successor to the Box Least Squares (BLS) algorithm, which has served as a standard tool for the detection of periodic transits. In this proof-of-concept paper, we demonstrate how TLS finds small planets that have previously been missed. We showcase TLS' capabilities using the K2 EVEREST-detrended light curve of the star K2-32 (EPIC205071984) that was known to have three transiting planets. TLS detects these known Neptune-sized planets K2-32b, d, and c in an iterative search and finds an additional transit signal with a high signal detection efficiency (SDE_TLS) of 26.1 at a period of 4.34882 (-0.00075, +0.00069) d. We show that this signal remains detectable (SDE_TLS = 13.2) with TLS in the K2SFF light curve of K2-32, which includes a less optimal detrending of the systematic trends. The signal is below common detection thresholds, however, if searched with BLS in the K2SFF light curve (SDE_BLS = 8.9) as in previous searches. Markov Chain Monte Carlo sampling shows that the radius of this candidate is 1.01 (-0.09, +0.10) Earth radii. We analyze its phase-folded transit light curve using the vespa software and calculate a false positive probability FPP = 3.1e-3, formally validating K2-32e as a planet. Taking into account the multiplicity boost of the system, FPP < 3.1e-4. K2-32 now hosts at least four planets that are very close to a 1:2:5:7 mean motion resonance chain. The offset of the orbital periods of K2-32e and b from a 1:2 mean motion resonance is in very good agreement with the sample of transiting multi-planet systems from Kepler, lending further credence to the planetary nature of K2-32e. We expect that TLS can find many more transits of Earth-sized and smaller planets in the Kepler data that have hitherto remained undetected with BLS and similar algorithms.Comment: published in A&A, Vol. 625, id. A31 , 8 pages, 6 colored figure

Revisiting the exomoon candidate signal around Kepler-1625b

Transit photometry of the exoplanet candidate Kepler-1625b has recently been interpreted to show hints of a moon. We aim to clarify whether the exomoon-like signal is really caused by a large object in orbit around Kepler-1625b. We explore several detrending procedures, i.e. polynomials and the Cosine Filtering with Autocorrelation Minimization (CoFiAM). We then supply a light curve simulator with the co-planar orbital dynamics of the system and fit the resulting planet-moon transit light curves to the Kepler data. We employ the Bayesian Information Criterion (BIC) to assess whether a single planet or a planet-moon system is a more likely interpretation of the light curve variations. We carry out a blind hare-and-hounds exercise using many noise realizations by injecting simulated transits into different out-of-transit parts of the original Kepler-1625 data: 100 sequences with 3 synthetic transits of a Kepler-1625b-like planet and 100 sequences with 3 synthetic transits of this planet with a Neptune-sized moon. The statistical significance and characteristics of the exomoon-like signal strongly depend on the detrending method, and the data chosen for detrending, and on the treatment of gaps in the light curve. Our injection-retrieval experiment shows evidence for moons in about 10% of those light curves that do not contain an injected moon. Strikingly, many of these false-positive moons resemble the exomoon candidate. We recover up to about half of the injected moons, depending on the detrending method, with radii and orbital distances broadly corresponding to the injected values. A $\Delta$BIC of -4.9 for the CoFiAM-based detrending indicates an exomoon around Kepler-1625b. This solution, however, is only one out of many and we find very different solutions depending on the details of the detrending method. It is worrying that the detrending is key to the interpretation of the data.Comment: 16 pages, 12 figures. Accepted for publication by A&

Detection of exomoons in simulated light curves with a regularized convolutional neural network

Many moons have been detected around planets in our Solar System, but none has been detected unambiguously around any of the confirmed extrasolar planets. We test the feasibility of a supervised convolutional neural network to classify photometric transit light curves of planet-host stars and identify exomoon transits, while avoiding false positives caused by stellar variability or instrumental noise. Convolutional neural networks are known to have contributed to improving the accuracy of classification tasks. The network optimization is typically performed without studying the effect of noise on the training process. Here we design and optimize a 1D convolutional neural network to classify photometric transit light curves. We regularize the network by the total variation loss in order to remove unwanted variations in the data features. Using numerical experiments, we demonstrate the benefits of our network, which produces results comparable to or better than the standard network solutions. Most importantly, our network clearly outperforms a classical method used in exoplanet science to identify moon-like signals. Thus the proposed network is a promising approach for analyzing real transit light curves in the future

An alternative interpretation of the exomoon candidate signal in the combined Kepler and Hubble data of Kepler-1625

Kepler and Hubble photometry of a total of four transits by the Jupiter-sized Kepler-1625b have recently been interpreted to show evidence of a Neptune-sized exomoon. The profound implications of this first possible exomoon detection and the physical oddity of the proposed moon, that is, its giant radius prompt us to re-examine the data and the Bayesian Information Criterion (BIC) used for detection. We combine the Kepler data with the previously published Hubble light curve. In an alternative approach, we perform a synchronous polynomial detrending and fitting of the Kepler data combined with our own extraction of the Hubble photometry. We generate five million MCMC realizations of the data with both a planet-only model and a planet-moon model and compute the BIC difference (DeltaBIC) between the most likely models, respectively. DeltaBIC values of -44.5 (using previously published Hubble data) and -31.0 (using our own detrending) yield strongly support the exomoon interpretation. Most of our orbital realizations, however, are very different from the best-fit solutions, suggesting that the likelihood function that best describes the data is non-Gaussian. We measure a 73.7min early arrival of Kepler-1625b for its Hubble transit at the 3 sigma level, possibly caused by a 1 day data gap near the first Kepler transit, stellar activity, or unknown systematics. The radial velocity amplitude of a possible unseen hot Jupiter causing Kepler-1625b's transit timing variation could be some 100m/s. Although we find a similar solution to the planet-moon model as previously proposed, careful consideration of its statistical evidence leads us to believe that this is not a secure exomoon detection. Unknown systematic errors in the Kepler/Hubble data make the DeltaBIC an unreliable metric for an exomoon search around Kepler-1625b, allowing for alternative interpretations of the signal.Comment: 8 pages, 5 figures (4 col, 1 b/w), 1 Table, published in A&A, Vol. 624, A9

Exomoon indicators in high-precision transit light curves

While the solar system contains about 20 times more moons than planets, no moon has been confirmed around any of the thousands of extrasolar planets known so far. Tools for an uncomplicated identification of the most promising exomoon candidates could be beneficial to streamline follow-up studies.} Here we study three exomoon indicators that emerge if well-established planet-only models are fitted to a planet-moon transit light curve: transit timing variations (TTVs), transit duration variations (TDVs), and apparent planetary transit radius variations (TRVs). We re-evaluate under realistic conditions the previously proposed exomoon signatures in the TTV and TDV series. We simulate light curves of a transiting exoplanet with a single moon. These model light curves are then fitted with a planet-only transit model, pretending there were no moon, and we explore the resulting TTV, TDV, and TRV series for evidence of the moon. The previously described ellipse in the TTV-TDV diagram of an exoplanet with a moon emerges only for high-density moons. Low-density moons distort the sinusoidal shapes of the TTV and the TDV series due to their photometric contribution to the combined planet-moon transit. Sufficiently large moons can produce periodic apparent TRVs of their host planets that could be observable. We find that Kepler and PLATO have similar performances in detecting the exomoon-induced TRV effect around simulated bright ($m_V=8$) stars. These stars, however, are rare in the Kepler sample but will be abundant in the PLATO sample. Moreover, PLATO's higher cadence yields a stronger TTV signal. The periodogram of the sequence of transit radius measurements can indicate the presence of a moon. The TTV and TDV series of exoplanets with moons can be more complex than previously assumed. We propose that TRVs could be a more promising means to identify exomoons in large exoplanet surveys.Comment: 13 pages, 9 figures, 1 tabl

Transit least-squares survey -- III. A 1.9 R⊕1.9\,R_\oplus transit candidate in the habitable zone of Kepler-160 and a nontransiting planet characterized by transit-timing variations

The Sun-like star Kepler-160 (KOI-456) has been known to host two transiting planets, Kepler-160 b and c, of which planet c shows substantial transit-timing variations (TTVs). We used the archival Kepler photometry of Kepler-160 to search for additional transiting planets using a combination of our Wotan detrending algorithm and our transit least-squares (TLS) detection algorithm. We also used the Mercury N-body gravity code to study the orbital dynamics of the system. First, we recovered the known transit series of planets Kepler-160 b and c. Then we found a new transiting candidate with a radius of 1.91 (+0.17, -0.14) Earth radii (R_ear), an orbital period of 378.417 (+0.028, -0.025) d, and Earth-like insolation. The vespa software predicts that this signal has an astrophysical false-positive probability of FPP_3 = 1.8e-3 when the multiplicity of the system is taken into account. Kepler vetting diagnostics yield a multiple event statistic of MES = 10.7, which corresponds to an ~85 % reliability against false alarms due to instrumental artifacts such as rolling bands. We are also able to explain the observed TTVs of planet c with the presence of a previously unknown planet. The period and mass of this new planet, however, do not match the period and mass of the new transit candidate. Our Markov chain Monte Carlo simulations of the TTVs of Kepler-160 c can be conclusively explained by a new nontransiting planet with a mass between about 1 and 100 Earth masses and an orbital period between about 7 and 50 d. We conclude that Kepler-160 has at least three planets, one of which is the nontransiting planet Kepler-160 d. The expected stellar radial velocity amplitude caused by this new planet ranges between about 1 and 20 m/s. We also find the super-Earth-sized transiting planet candidate KOI-456.04 in the habitable zone of this system, which could be the fourth planet.Comment: published in A&A, 15 pages, 11 Figures (7 col, 4 b/w), 2 Table